AVP - Gen AI - Fraud Analytics DS

As a Specialized Analytics Senior Analyst at our company, you will be a seasoned professional contributing to the development of new techniques and processes within the area of generative AI solutions for Fraud prevention. Your role will involve integrating subject matter expertise, collaborating with cross-functional teams, and mentoring junior team members. Your responsibilities will include designing, developing, and deploying AI solutions, customizing RAG frameworks, conducting research to advance generative modeling, optimizing model performance, implementing AI pipelines, and presenting project progress to stakeholders. Key Responsibilities: - Design, Develop and deploy generative AI based solutions for various Fraud prevention areas. - Customize and fine-tune existing RAG frameworks or design new RAG to meet project requirements. - Collaborate with cross-functional team to understand business requirements and translate them into AI solutions. - Conduct research to advance the state-of-the art in generative modeling and stay up to date with latest advancements in the field. - Optimize and fine-tune models for performance, scalability, and robustness. - Strong experience in prompt engineering. - Implement and maintain AI pipelines and infrastructure to support model training and deployment. - Perform data analysis and preprocessing to ensure high-quality input for model training. - Mentor junior team members and provide technical guidance. - Write and maintain comprehensive documentation for models and algorithms. - Present findings and project progress to stakeholders and management. - Experience with cloud platforms such as AWS, Google Cloud, or Azure. - Knowledge of reinforcement learning and its applications in generative AI. - Familiarity with MLOps practices and tools. - Contributions to open-source projects or published research in top-tier conferences/journals. Qualifications: - 8+ years of experience in machine learning and deep learning, with a focus on generative models. - Strong proficiency in Python and deep learning frameworks such as TensorFlow, PyTorch, or Keras. - Experience working with Model Risk Management team for model approval and governance related work. - Proven track record of building and deploying generative models-based solutions in production environments. - Solid understanding of machine learning algorithms, data structures, and software engineering principles. - Excellent problem-solving skills and the ability to work independently and as part of a team. - Ability to build partnerships with cross-functional teams. - Working experience in a quantitative field, specifically in the Financial/Credit Card industry. - Willingness to learn and a can-do attitude. - Excellent communication and interpersonal skills, organized, detail-oriented, flexible, and adaptive to a matrix work environment. Education: - Bachelors or masters degree in computer science, Data Science, Machine Learning, or a related field. A Ph.D. is a plus.,